Diagnostic methods for osteoporosis

ABSTRACT

Methods of diagnosing bone disease such as osteoporosis are provided. The methods comprise detecting changes in the physical or chemical structure of a keratinized tissue as correlates of disease. The methods include detecting changes in the hardness, modulus, or level of sulfur bonding, particularly the level of disulfide bonding, in a keratinized tissue sample such as nail, hair, or skin. Changes in these variables serve as diagnostic markers of bone diseases that are associated with changes in bone elasticity and bone density.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.11/570,669, filed Sep. 11, 2007, which is a national stage entry ofInternational Patent Application Serial No. PCT/EP05/06694, filed onJun. 20, 2005, which claims priority to U.S. Provisional PatentApplication Ser. No. 60/581,807, filed on Jun. 22, 2004, the contents ofeach of which are incorporated by reference.

FIELD OF THE INVENTION

The present invention relates to methods of diagnosing osteoporosis bydetecting physical and chemical changes in keratinized tissues.

BACKGROUND OF THE INVENTION

Osteoporosis is a disease characterized by a deficiency of bone thataffects both the protein matrix and the mineral fraction, resulting in adecrease in the resistance of bones to fracture. The current method ofdiagnosis is by means of dual energy x-ray absorptiometry (DEXA), whichprovides a quantitative measurement of the amount of mineral present inbone and allows determination of fracture risk at a measured site. Adecrease in bone mineral density (BMD) as measured by DEXA is thecurrent method of diagnosing osteoporosis and predicting fractures. See,for example, Nevitt and Cummings (1993) J. Am. Geriatr. Soc. 41:1226;and Parfitt (1993) Calcif. Tissue Int. 53:S82. However, the lack ofperfect correlation between bone mineral density and bone fracturessuggests that low bone mineral density is not the only cause of fragilebones (Ott (1993) Calcif. Tissue Int. 53(Suppl.):S7). Thus, while thedegree of mineralization is the current standard by which osteoporosisis diagnosed, it is unable to detect bone fragility due to deficiency inprotein matrix.

Bone is a composite material, comprising mineral, organic, and waterphases (Katz (1971) J. Biomech. 4:455). The mineral phase, mainlyhydroxyapatite (HA), imparts compressive strength, while the organicphase, collagen, imparts flexibility. Wang et al. (1998) Bone 23:67 haveshown that with increasing age, the fracture toughness of bone isdecreased and its microhardness increased without significant changes inBMD. McCalden et al. reported similar findings, indicating that evenwithout significant changes in BMD, the tensile strength of bone candecrease with age due to increased porosity (McCalden et al. (1993) J.Bone Joint Surg. 75A:1193). There is now a belief that the organic phaseof bone plays a significant role in osteoporosis. Kovach et al. haveshown that changes in the structural characteristics of the collagennetwork detected using a laser fluorescence technique correlatesignificantly with bone fracture toughness (Kovach et al. (1997)Proceedings of the 43th Annual Meeting of the Orthopaedic ResearchSociety, San Francisco, Calif., 22:37). This work is supported by otherfindings demonstrating that the organic phase of bone is responsible formuch of its ability to resist fracture (Wang et al. (1998) Proceedingsof the 44th Annual Meeting of the Orthopaedic Research Society, NewOrleans, La.; and Wang et al. (2002) Bone 31:1). Mansell and Baileyfound that collagen in osteoporotic bone is not normal but insteadcontains higher levels of lysine hydroxylation and modifiedcross-linking (Mansell and Bailey (2003) Int. J. Biochem. Cell Biol.35:522). This and other studies have shown that osteoporosis has adegenerative effect on proteiri production in bones with increasedimmature collagen cross-links, increased collagen synthesis anddegradation (increased turnover despite overall loss of collagen), aswell as reduced mineralization (Oxlund (1996) Bone 19:479; and Bailey(2002) J. Musculoskel. Neuron Interact. 2:529). The increasedhydroxylation leads to the formation of finer fibrils with alteredcrosslinks, and reduced calcification, which further contributes to thefragility of the bone.

One study examined the calcium and magnesium levels in bone and nails(Vecht-Hart et al. (1995) Clin. Chim. Acta 236:1). No correlation wasfound to exist between the two. Other research examined the relationshipbetween mineral concentrations in nail and bone, and the results havesuggested that significant correlations exist between zinc levels andBMD (r=−0.399) and between the ratio of Zn/Ca to BMD (r=0.421) (Karitaand Takano (1994) Nippon Koshu Eisei Zasshi 41:759). Nevertheless, theseassays all examine the inorganic component of bone and nails, and do notcorrelate changes in the protein chemistry or structure that may also bepresent in the disease state.

Bone densitometry is the current gold standard for diagnosis of bonediseases such as osteoporosis. However, this method is limited tomeasuring bone mass, and it does not take into consideration themicroarchitecture of the bone, the crystal organization, size and shape,the connectivity of the trabecullar network, and the structure of thebone proteins. Moreover, DEXA is a relatively expensive diagnosticprocedure that exposes the patient to potentially harmful x-rays; thusit cannot be used for mass screenings, such as at routine checkups.Therefore, clinicians risk under diagnosing patients at risk forfracture because the bone disease is often unrecognized until a fractureoccurs, or because bone mineral density does not always correlate with arisk of fragile bones even when DEXA is used. The alternative ofobtaining collagen from patient's bones is an even more expensive andrisky procedure. Thus, clinicians need new, low-risk methods to diagnosepatients that are at an increased risk of bone fracture.

BRIEF SUMMARY OF THE INVENTION

Methods useful in the diagnosis and prognosis of bone-related disorderssuch as osteoporosis are provided. The methods comprise measuringphysical and chemical changes of keratinized tissue as markers for thepresence of bone disease in a subject. The methods are especially usefulfor detecting osteoporosis and monitoring progression of bone disease.The methods disclosed herein can be also be used in prognostic assaysprior to, during, and after disease therapy. The disclosed prognosticassays are also useful for identifying subjects as candidates forvarious preferred means of therapeutic intervention.

The methods of the present invention comprise detecting physical andchemical changes in keratinized tissue that are predictive of thepresence of a bone disease that is associated with a change in boneelasticity or bone density. The physical and chemical changes include areduction in the hardness of a keratinized tissue, a reduction in themodulus of a keratinized tissue, or a reduction in the level of sulfurbonding in a keratinized tissue. Methods of detecting changes in thehardness and modulus of keratinized tissue include measuring thenanoindentation pressure and deformation of a keratinized tissue such asnail, hair, or skin. Methods of detecting changes in the level of sulfurbonding in keratinized tissue include using spectral analysis such asRaman spectroscopy to identify the relative abundance of disulfide bondsand carbon sulfide bonds in a keratinized tissue such as nail, hair, orskin. The advantages of examining a keratinized tissue such as nail,hair, or skin lies in the ability to assess properties other than thosemeasured by standard bone densitometry, the ease of access to suchsamples, and the rapid growth of keratinized tissue, which allowschanges to be monitored on a more frequent basis.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a schematic of a human fingernail. The nail clippings usedin Example 1 described herein were taken from the free edge of the nailplate.

FIG. 2 shows a schematic representation of a typical nanoindentationcurve comprising loading (a-b) and unloading (b-c-d) phases.

FIG. 3 shows a typical Raman spectrum of the human nail from 300cm⁻¹-1800 cm⁻¹.

FIG. 4 shows two Raman spectra, one from a non-osteoporotic (healthy)individual (top) and one from an osteoporotic individual (bottom).

FIG. 5 plots T-score as a function of age and bone quality test scorebased on the width at half maxima (WHM) for the S-S peak from the Ramanspectra for patients in the blind clinical trial referred to in Example2.

FIG. 6 plots fracture risk history as a function of age and bone qualitytest score base on WHM for the S-S peak from the Raman spectra forhealthy and at risk women.

FIG. 7 outlines the components of a Raman spectroscopy apparatus for usein obtaining Raman spectra from keratinized tissue samples such as nailseither in situ or as nail clippings for a subject undergoing testing fora bone disease such as osteoporosis.

DETAILED DESCRIPTION OF THE INVENTION

The present invention is directed to methods for diagnosis and prognosisof bone disease in a subject, where the disease is associated with achange in bone elasticity or bone density. The methods rely on detectionof physical and chemical changes in keratinized tissue as markers forthe presence of the bone disease of interest in a subject.

Without being bound by any mechanism or theory of action, it has beenfound that physical and chemical changes within a keratinized tissuecorrelate to the presence or absence of bone disease that is associatedwith changes in bone elasticity or bone density, such as osteoporosis.By “bone disease that is associated with changes in bone elasticity orbone density” is intended to mean any disease where the risk of bonefracture is increased due to structural and chemical changes in thebone. Examples of such diseases include but are not limited toosteoporosis, osteogenesis imperfecta, Paget's disease, and the like.These structural and chemical changes in bone are measurable by anymeans known in the art including but not limited to measurement of bonemineral density (BMD) and bone biopsy. The structural and chemicalchanges in bone correlate to changes in the level of sulfur bonding of akeratinized tissue or changes in the hardness or modulus of suchkeratinized tissue. The term “keratinized tissue” is intended to meanany biological sample comprising the protein keratin, more particularlyhard keratin. Keratinized tissue includes nail (fingernails andtoenails), hair, skin (i.e., epidermis), and the like. Measurements onkeratinized tissue samples may be made in situ (e.g., measurements madeon the attached nail, hair, or skin sample, including but not limited toskin on the hand, foot, arm, leg, torso, or face) or by collecting thekeratinized tissue sample (e.g., as clipped nails (also referred to asnail clippings), clipped hair, detached skin (i.e., epidermal peels orscrapings)) for measurement at a later time. The safety of obtainingkeratinized tissue samples such as nail, hair, or skin, coupled withtheir diagnostic power independent of bone mineral density and bonebiopsy make keratinized tissue-based diagnostic assays a useful newclinical tool.

The methods of the present invention generally comprise detectingchanges in the physical or chemical structure of the keratinized tissuesample and correlating a change (or lack of change) with a diagnosis ofbone disease. In some embodiments, the changes in physical or chemicalstructure of a keratinized tissue sample are used to assess whether thesubject has osteoporosis or other bone disease that is associated withchanges in bone elasticity or bone density and, thus, is at increasedrisk of bone fractures.

In other embodiments, the changes in physical or chemical structure of akeratinized tissue sample are used to assess the prognosis of a subjectwith osteoporosis or other bone disease that is associated with changesin bone elasticity or bone density. Because the presence or absence ofreduced bone mineral density is not in perfect correlation with the riskof bone fracture, changes in the physical or chemical structure ofkeratinized tissue may be used to assess additional risk factors such ascorrelating the likely progression of disease and prognosis of a subjectat increased risk of fracture.

Physical and chemical markers of interest include changes in thehardness or modulus of a keratinized tissue or changes in the level ofsulfur bonding within the keratinized tissue. Methods for detectingchanges in hardness or modulus of a keratinized tissue are well known inthe art and include but are not limited to nanoindentation and atomicforce microscopy. Methods for detecting changes in the level of sulfurbonding within a keratinized tissue are also well known in the art andinclude but are not limited to Raman spectroscopy, nuclear magneticresonance spectroscopy, Fourier transform infrared (FT-IR) spectroscopy,chiroptical techniques, mass spectroscopy, chromatography, reaction withother chemicals such as Elman's reagent, and the like. See, for example,Walker (2002) The Protein Protocols Handbook (Humana Press, Totowa).Those skilled in the art recognize that the diagnostic power of thevariables disclosed herein is not limited to a particular method ofdetection of the variable or changes thereof.

Keratin molecules are helical and fibrous. They form intermediatefilaments by twisting around each other to form strands. Keratincontains a high percentage of sulfur-containing amino acids, largelycysteine. These cysteines form disulfide bridges between the individualmolecules. The bridges cross-link the various secondary, tertiary, andquaternary keratin structures and thereby help maintain the structuralrigidity of keratinized tissue. “Hard” keratin, such as that in hair,nails, and skin (particularly the epidermal layer) has a greater amountof structural rigidity due to more disulfide bonds.

As disclosed herein, changes in hardness, modulus, or level of sulfurbonding of a keratinized tissue are correlated to bone disease.Therefore, changes in these physical and chemical properties ofkeratinized tissue may be used as diagnostic markers for bone diseasesthat are associated with changes in bone elasticity and bone density. Inone embodiment of the invention, a change in the hardness of akeratinized tissue is used to diagnose a patient with bone disease. Inother embodiments, a change in the modulus of a keratinized tissue isused to diagnose bone disease. In yet other embodiments, a change in thelevel of sulfur bonding in a keratinized tissue is used to diagnose bonedisease.

Modulus and hardness are measures of the brittleness of a keratinizedtissue, for example, nails, hair, or skin. By “modulus” is intendedstiffness or resistance of a keratinized tissue sample to deformation.By “hardness” is intended the extent to which a keratinized tissuesample is resistant to pressure. By “level of sulfur bonding” isintended the extent of the reduction (or, reciprocally, oxidation) ofsulfur-containing amino acids such as cysteine and methionine, morespecifically the extent to which the proteins form disulfide bridges orcarbon sulfide bonds.

The presence, absence, or extent of change in hardness, modulus, orlevel of sulfur bonding of a keratinized tissue sample, such as nails,hair, or skin, can be correlated to the presence, absence, or extent ofbone disease using methods standard in the art. See, for example, Zhouet al. (2002) Statistical Methods in Diagnostic Medicine (Wiley, NewYork). In one embodiment, the hardness of a keratinized tissue such asnails, hair, or skin provides a diagnostic criterion for bone fragilityand osteoporosis. In another embodiment, the modulus of a keratinizedtissue such as nails, hair, or skin provides a diagnostic criterion forbone fragility and osteoporosis. In other embodiments, the level ofsulfur bonding within a keratinized tissue such as nails, hair, or skinprovides a diagnostic criterion for bone fragility and osteoporosis. Infurther embodiments, the hardness, the modulus, or the level of sulfurbonding in a keratinized tissue such as nails, hair, or skin is used incombination with other diagnostic criteria previously known in the artsuch as bone mineral density tests (e.g., DEXA scans) and otherpreviously known clinical correlates to disease. As previously noted,measurements on keratinized tissue samples may be made in situ (e.g.,measurements made on the attached nail, hair, or skin sample) or bycollecting the keratinized tissue sample (e.g., as clipped nails (alsoreferred to as nail clippings), clipped hair, detached skin (i.e.,epidermal peels or scrapings)) for measurement at a later time.

In one embodiment, the hardness or modulus of a keratinized tissuesample is measured by a method termed “nanoindentation” using a machinepreviously described by Arteaga et al. (1993) Tribology Intl. 26:305. Inthis method, force is applied to a keratinized tissue sample and theresistance measured. In one such embodiment, the keratinized tissuesample is nails (fingernails or toenails), either attached (i.e.,measurement performed in situ) or clipped. Where nail clippings are tobe measured, the nail clippings are collected from the free edge of thenail plate as shown in FIG. 1. Following collection, nanoindentation isused to detect hardness or modulus of the nail clippings. Preferably thenail clippings are subjected to nanoindentation within 1 day to withinone month of collection, more preferably within 1 day to within threeweeks of collection. In some embodiments, the nail clippings aresubjected to nanoindentation within 1 day to within two weeks ofcollection; in other embodiments, the nail clippings are subjected tonanoindentation within 1 day to within one week, preferably within 1 dayto within 3 days of collection. Where nail clippings are to be storedfor future analysis, they are collected and stored in sealed jars tominimize changes in hydration following nail clipping collection.

Following collection of the nail clippings, the clippings are subjectedto nanoindentation to assess hardness and modulus of this keratinizedtissue. More specifically, pressure and release cycle readings are takenof the displacement of the indenter δ, and the load P, allowing theexamination of force-penetration data during both the loading andunloading phases. A curve measuring the penetration depth at each forcelevel during the loading and unloading phases can then be generated.

In this manner, the modulus can be defined as the linear section of thenanoindentation unloading curve (b-c in FIG. 2).

In some embodiments, the hardness, H, is defined as

$\begin{matrix}{H = \frac{P}{A}} & \left( {{Formula}\mspace{14mu} 1} \right)\end{matrix}$where P is the force applied to the indenter and A is the projected areaof the contact. In nanoindentation, the projected area of contact iscalculated from the geometry of the indenter and the measured depth ofpenetration in contact with the indenter, h, using the machine disclosedby Arteaga et al. (1993) Tribology Intl. 26:305, whereA=kh ²  (Formula 2)and where k is a constant dependant upon the geometry and type ofindenter used. In some embodiments, the indenter is a trigonal diamondpyramid with an equilateral triangular cross-section and a 90° anglebetween each face and the opposing edge (the corner of a cube). For thisindenter k=2.6. Substituting (Formula 2) into (Formula 1) gives:

$\begin{matrix}{H = \frac{P}{2.6 \cdot \delta_{p}^{2}}} & \left( {{Formula}\mspace{14mu} 3} \right)\end{matrix}$

While the indenter is moving into the material, the load P has toprovide the stress field which is necessary to support the plastic flowof material out of the indentation as well as the static pressure equalto the hardness. Due to this, the curve of dynamic hardness as afunction of depth derived from (Formula 1) usually has a very high valueat small depths where the strain rate, which is proportional to 1/δdδ/dt, is greatest. In some embodiments, a single hardness number isquoted from the results and this is taken as the maximum applied forcewhere the strain rate is a minimum.

Though the foregoing discussion of nanoindentation is directed to nailclippings, the methodology is also applicable to attached nails, as wellas to other keratinized tissues including hair and skin, which can bemeasured in situ or on collected tissue samples that are handled in amanner similar to that described above for nail clippings. In thismanner, keratinized tissue is collected, for example, clipped hair ordetached skin tissue, and the collected tissue sample is subjected tonanoindentation within 1 day to within one month of collection, morepreferably within 1 day to within three weeks of collection. In someembodiments, the keratinized tissue is collected and the collectedtissue sample is subjected to nanoindentation within 1 day to within twoweeks of collection; in other embodiments, the keratinized tissue iscollected and the collected tissue sample is subjected tonanoindentation within 1 day to within one week, preferably within 1 dayto within 3 days of collection. As previously noted above for nailclippings, where keratinized tissue is to be stored for future analysis,tissue samples are collected and stored in sealed jars to minimizechanges in hydration following tissue collection.

In another embodiment, level of sulfur bonding within a keratinizedtissue such as nails, hair, or skin is measured, either in situ orfollowing collection of the keratinized tissue sample. Of particularinterest is the extent of disulfide bridge formation between cysteinemolecules in the keratinized tissue. The extent of crosslinking ofcysteine via oxidized thiols (also known as the formation of cystine)correlates with the hardness or modulus of keratinized tissue asdiscussed supra. In one such embodiment, the extent of disulfide bridgeformation is measured by means of spectral analysis, for example, usingRaman spectroscopy, nuclear magnetic resonance spectroscopy, FT-IRspectroscopy, chiroptical techniques, mass spectroscopy, chromatography,reaction with other chemicals such as Elman's reagent, and the like.

Raman spectroscopy is a widely used tool for qualitative andquantitative analysis of materials. It relies on a spectral shift thatoccurs when light is projected onto a material to be tested and thendeflected off the material surface. In laser Raman spectroscopy,monochromatic laser light that is deflected or scattered off the testmaterial surface is detected by a sensitive detection system. Themajority of the light deflected off the surface is scattered elasticallyat the same wavelength as the original light source in a process knownas Rayleigh scattering. The remainder of the deflected light isscattered inelastically at a wavelength that differs from the originallight source in a process known as Raman scattering. The two types ofscattered light are separated from each other using any suitablewavelength selection system, such as prisms, filters, or opticalgratings. The resulting Raman spectrum can be used to identify andquantify concentrations of various substances within the test materialof interest. Raman scattering detected from a keratinized tissue samplecan be used to identify individuals having or at risk of developing abone disease such as osteoporosis.

In this manner, a keratinized tissue sample, such as nail (i.e.,fingernail or toenail), hair, or skin (measured in situ or on a tissuesample collected as described above) is irradiated by a light sourcesuch as a laser, and then the wave number and intensity of theinelastically scattered light is measured. In one embodiment, thekeratinized tissue sample is nail. Raman spectra of human nails areknown (Akhtar and Edwards (1997) Spectrochimica Acta A53:81; and Edwardset al. (1998) Spectrochimica Acta A54:745). The Raman spectra reflectthe bonding arrangements in the molecular makeup of a keratinized tissuesuch as nail, hair, or skin. Although the Raman spectrum can coverbetween 300 cm⁻¹ and 1800 cm⁻¹, particular peaks in this spectrumcorrespond to specific chemical structures of interest to the methods ofthe present invention. For sulfur bonding, the area of interest isgenerally between 400 cm⁻¹ and 700 cm⁻¹. For example, in human nails,three peaks correspond to sulfur bonds present in keratin, the mostabundant protein in nails, specifically the disulfide bond (S-S,gauche-gauche-gauche conformation) at 510 cm⁻¹ and the carbon sulfidebond (C-S) at about 621 cm⁻¹ and 643 cm⁻¹. These Raman spectra can beused alone or in combination to indicate the extent to which cysteine isoxidized to form disulfide bridges in a keratinized tissue sample.

Thus, in some embodiments, the Raman spectra measurements are conductedon nails (i.e., fingernails or toenails) in situ or on nail clippings.Any Raman spectroscopy apparatus known in the art can be used to analyzethe nails. See, for example, the non-invasive Raman spectroscopyapparatus for in situ measurements of carotenoid levels in livingtissues described in U.S. Pat. Nos. 5,873,831 and 6,205,354, hereinincorporated by reference in their entirety, and a modification of thisapparatus as described in Example 3 herein below. Such an apparatusspecifically designed for non-invasive measurement of sulfide bondlevels in a keratinized tissue sample such as nails, particularly thelevel of disulfide bonding corresponding to the peak appearing at 510cm⁻¹ of the Raman spectrum, comprises the following components: (1) ameans for generating light within a wavelength giving a Raman responsewith a wavelength shift for the disulfide bond to be detected; (2) adelivery means for directing this light onto the fingernail, where thislight has an intensity that does not damage the fingernail and does notalter disulfide bond levels; (3) a collection means for collecting lightscattered from the fingernail; (4) spectrally selective means forselecting Raman shifted light from the scattered light collected by thecollection means; (5) detection means for scanning and measuring theRaman shifted light at frequencies characteristic of disulfide bonds;and (6) quantifying means for determining Raman signal intensity for thedisulfide bonds.

As the Raman shift is independent of the wavelength of incident lightused, any strong and fairly monochromatic light source can be used inthis technique. Thus, for example, the means for generating light can bea laser light source; alternatively, other means include, but are notlimited to, light sources that generate monochromatic light, and anyother light projection system. Various delivery means and collectionmeans can be used, including, for example, optical components fordirecting a beam of light from the light source to the nail to bemeasured, either in situ or as a nail clipping, and for collecting thescattered light. The collected scattered light can be spectrallyselected, for example, using a Raman spectrometer that separates theRaman scattered light from Rayleigh scattered light. Thus, thespectrally selective system can comprise various optical components,including, but not limited to, prisms, grating monochromators, andfilters such as holographic filters, dielectric filters, acousto-opticfilters, combinations thereof, and the like. The light detection systemis capable of measuring the intensity of the Raman scattered light as afunction of frequency in the frequency range of interest, i.e., at 510cm⁻¹ for detecting the level of disulfide bonding in the nail sample.Components within the light detection system include, but are notelimited to, a photomultiplier apparatus, photodiodes, devices such as acharge coupled device (CCD) detector array, anintensified CCD detectorarray, and the like. Preferably the light detected by the lightdetection system is converted into a signal that can be displayedvisually, for example, on a computer monitor or the like, or isconverted into other digital or numerical formats. The resultant Ramansignal intensities are preferably analyzed via a quantifying means suchas a quantifying system, which may be calibrated, for example, bycomparison with spectra obtained from other samples of interest or otherpeaks on the same sample. In some embodiments, the quantifying system isa computer that comprises spectral data acquisition software installedso that spectral analysis can be manipulated, for example, to removebackground noise and the like. For further details on exemplarycomponents that can be included in a Raman spectroscopy apparatus formeasurements of level of sulfur bonding, particularly disulfide bonding,in keratinized tissue samples in situ, see U.S. Pat. Nos. 5,873,831 and6,205,354, herein incorporated by reference in their entirety.

In another embodiment, FT-IR (Fourier transform-infrared) is used tomeasure the level of sulfur bonding in a keratinized tissue sample suchas nail, hair, or skin, where the keratinized tissue is measured in situor on a collected keratinized tissue sample. Those skilled in the artrecognize that infrared covers a slightly different region of thespectrum than Raman spectroscopy. However methods of configuring theFT-IR apparatus to cover this area of the spectrum are well known in theart.

A number of ways of interpreting spectral data are known in the art andare thus suitable for the diagnostic methods disclosed herein. Thus, forexample, spectral data obtained from Raman spectroscopy can be analyzedfor differences between control versus test biological samples at anygiven spectral peak of interest, for example, the peak at 510 cm⁻¹corresponding to disulfide bonds (S-S, gauche-gauche-gaucheconformation) and the peaks at about 621 cm⁻¹ and 643 cm⁻¹ correspondingto carbon sulfide bonds (C-S). At any given spectral peak, thedifference between a control and test biological sample can be analyzedbased upon a comparison of the width at half maximum height of the peak,the relative peak height, area integration (i.e., area under the peak),combinations thereof, and the like. In some embodiments, the diagnosticassays described herein are based on comparisons of the width at halfmaximum height (WHM) of the Raman spectral peak that corresponds todisulfide bonds of a keratinized tissue such as nail, hair, or skin(i.e., the peak at about 510 cm⁻¹). However, it is recognized that anymethodology can be utilized to compare differences in the Raman spectraobtained from keratinized tissue samples, for example, differencesoccurring at the spectral peak appearing at about 510 cm⁻¹.

Those skilled in the art recognize that diagnostic assays can bedescribed in terms of accuracy. The term “accuracy” is intended to meanthe total number of results of a given test divided by the number ofincorrect results. Incorrect results are a function of error ratespresent in the assay and include but are not limited to measurementerror, user error, reporting error, and the like. Diagnostic assays canbe further described in terms of false positive and false negativerates. False positive and false negative rates are generated bycomparing the results of an assay against a gold standard. By the term“gold standard” is intended a reference standard that is unlikely to beincorrect or has been traditionally used to define the disease, such asbone mineral density for osteoporosis. False positive and false negativerates affect the sensitivity and specificity of an assay.

The sensitivity of a test is the probability that it will produce a truepositive result when used on a diseased population (as compared to areference or “gold standard”). The sensitivity of a diagnostic test iscalculated as: (the number of true positive results)/(the number of truepositive results+the number of false negative results). The specificityof a test is the probability that a test will produce a true negativeresult when used on a non-diseased population (as determined by areference or “gold standard”). The specificity of a test is calculatedas: (the number of true negative results)/(the number of true negativeresults+the number of false positive results). The sensitivity andspecificity of a diagnostic test indicates possible uses within aparticular population. For example, high sensitivity tests are useful inscreening populations where the disease to be diagnosed is relativelyserious and the treatment is relatively inexpensive and readilyavailable because the cost of a failing to detect a diseased patient ishigh (false negative) and the cost of treating an undiseased patient islow (false positive). Alternatively, high specificity tests are usefulin screening populations where the disease is not as serious and thetreatment is relatively expensive because the few undiagnosed, diseasedpatients (false negatives) within the population will not suffer greatlyas compared to the unnecessary treatment of many non-diseased patients(false positives). It is routine within the art to adjust thespecificity and sensitivity of assays or use variant assays withdiffering sensitivity and specificity to screen specific populations.The sensitivity of the disclosed methods for the detection of a bonedisease such as osteoporosis is at least about 70%, preferably at leastabout 75%, 80%, 85%, more preferably at least about 90, 91, 92, 93, 94,95, 96, 97, 98, 99% or more, depending upon the diagnostic method used.Furthermore, the specificity of the present methods for detection is atleast about 50%, preferably at least about 60%, 70%, 75%, 80%, morepreferably at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99% ormore, depending upon the diagnostic method used.

Measurements of hardness, modulus, or level of sulfur bonding in akeratinized tissue sample find use in screening any population in needof treatment. Those skilled in the art are routinely able to determinethe false negative and false positive rates of these assays. Also, thoseskilled in the art recognize that statistical measures such as accuracy,specificity, and sensitivity are equally applicable to continuous aswell as nominal variables. Thus, the diagnostic methods described hereincan be used to assess not only the presence or absence of disease (i.e.,nominal variable) but also the extent or severity of disease (i.e.,continuous variable).

Those skilled in the art also recognize that results of the individualdiagnostic assays disclosed herein can be combined with other assayspreviously known in the art to further refine the accuracy, specificity,and sensitivity of the diagnosis. Thus, the assays disclosed herein maybe used in conjunction with such other diagnostic indicators such asclinical presentation, decrease in bone mineral density, radiographicevidence of osteopenia or vertebral deformity, loss of height, thoracickyphosis, previous fragility fracture, prolonged corticosteroid therapy,premature menopause, prolonged secondary amenorrhea, primaryhypogonadism, chronic disorders associated with osteoporosis (e.g.,anorexia nervosa, malabsorption syndromes), maternal history of hipfracture, serum prevalence of C-telopeptide of type I collagen, lowcalcaneal ultrasonic variables (BUA and SOS), low body mass index, andthe like.

Those skilled in the art also recognize that the diagnostic assaysdescribed herein may be routinely used for prognostic assays.Specifically, the results of a diagnostic assay (e.g., changes inhardness, modulus, or level of sulfur bonding in a keratinized tissuesample) can be correlated to another variable (or combination ofvariables) of interest, such as the mean time before death, the recoveryrate, the relapse rate, the progression rate, the severity of disease,the treatment response rate, molecular diagnostics, and the like, topredict a clinical outcome. Both historical and contemporaneous data onpatients are routinely available. These data may be positively ornegatively correlated with changes in hardness, modulus, or level ofsulfur bonding of a keratinized tissue sample.

The statistical relationships between the results of the diagnosticassay and a known outcome are useful in generating a correlationcoefficient, which indicates the magnitude of a correlation as comparedto a random association between variables. See, for example, Zhou et al.(2002) Statistical Methods in Diagnostic Medicine (Wiley, New York).Other methods of correlating relationships are known in the art andthese methods may all find use in the methods disclosed herein.

In some embodiments, the prognostic assays disclosed herein are used tostratify osteoporosis patients with increased risk of bone fracture. Theterm “stratify” is intended to mean that a group sharing a commoncharacteristic, such as having osteoporosis, is subdivided into one ormore subclasses.

To determine changes in the physical or chemical structure of akeratinized tissue sample and thereby detect (by any method known in theart including but not limited to the assays disclosed and incorporatedby reference herein) the presence of bone disease, or stage of bonedisease, such as osteoporosis, the signal generated from a test of thephysical or chemical structure of a keratinized tissue sample isgenerally compared to a threshold signal that corresponds to apredetermined cut-off value. In one embodiment, the cut-off value forthe detection of a change in hardness, modulus, or level of sulfurbonding in a keratinized tissue sample is the average signal obtainedfrom keratinized tissue samples collected from subjects without bonedisease, for example, those without osteoporosis.

Generally, detecting a decrease (relative to a control sample) in thehardness or modulus of a keratinized tissue sample or a decrease in thelevel of sulfur bonding in a keratinized tissue sample is indicative ofa bone disease, or more specifically fragile bones, such as those foundin osteoporosis patients. Physicians can use the assays disclosed hereinto generate information that can assist in choosing to initiate, change,or increase/decrease therapeutic regimens, as discussed supra. Inaddition, a physician may use information provided by the assaysdisclosed herein to confirm or exclude potential diagnoses based onother diagnostic methods including bone mineral density and otherdiagnostics.

In some embodiments, the keratinized tissue sample is nail, and Ramanspectroscopy is utilized to predict the presence or absence ofosteoporosis in a subject. In this manner, a Raman spectrum is collectedon nails (in situ or nail clippings) of the subject to be tested, andthe level of disulfide bonding is detected by analyzing the intensity ofthe peak at 510 cm⁻¹ of the Raman spectrum. As noted above, intensity ofthis peak can be determined using any method of spectral analysis knownin the art. The intensity of this peak represents a bone quality scorefor the individual and is indicative of the presence or absence of, orrisk of developing, osteoporosis. In one embodiment, the intensity ofthe peak at 510 cm⁻¹ of the Raman spectrum for nails is calculated basedon the width at half maximum (WHM) value of this peak. A mean WHM valueat or above about 35 cm⁻¹ is indicative of an individual having a bonemineral density (BMD) T-score of ≦−1.5 (as measured by DEXA; see FIG.5). In accordance with the World Health Organization's definition andcategorization of osteoporosis, a BMD T-score of ≦−1.5 is indicative oflow bone mass, while a BMD T-score of ≦−2.5 indicates the presence ofosteoporosis. The sensitivity of this diagnostic test to predict a BMDT-score of ≦−2.5 (and thus presence of osteoporosis) in a population of52 women participating in a blind clinical trial was 93.3%, while thespecificity of the test to predict this BMD T-score was 95.5% (seeExample 2 herein below).

In other embodiments, a mean WHM value at or above about 35 cm⁻¹ for thepeak at 510 cm⁻¹ of the Raman spectrum for nails is indicative of anindividual who is at risk for fracture, for example, fracture associatedwith a bone disease such as osteoporosis (see FIG. 6). Where anindividual tests positive (for example, a mean WHM value at or aboveabout 35 cm⁻¹ for the peak at 510 cm⁻¹ of the Raman spectrum for nailsamples), proactive medical therapy to slow loss of bone mass, diseaseprogression, and to reduce fracture risk can be implemented. One ofskill in the art will recognize that subsequent diagnostic assaysconducted in a similar manner, e.g., spectral analysis of a keratinizedtissue such as nails, for an individual undergoing medical therapy forthe bone disease, can provide a means of monitoring treatment efficacy.

The following examples are offered by way of illustration and not by wayof limitation.

EXPERIMENTAL

The current noninvasive testing methods for osteoporosis use dual energyx-ray absorptiometry (DEXA) scanners or ultrasound-based scans thatmeasure bone density. These tests require expensive diagnostic equipmentand trained personnel, thereby limiting their application.

The diagnostic assays described in Example 1 below represent novelnoninvasive diagnostic tests for osteoporosis, which for purposes ofthis invention are referred to as Bone Quality Tests (BQT). A BQTmeasures the chemical properties (microarchitecture) of a keratinizedtissue such as the nail as opposed to measuring bone density. The BQT isbased on the finding that there is a statistically significantdifference in the state of the proteins, particularly keratin, betweenthe nails of a healthy person and those of a person with osteoporosis.Thus, the microarchitecture of the nail can be used as an analogue forbone quality.

The BQT is a much simpler methodology, and is potentially more costeffective, than other forms of noninvasive osteoporosis detectionmethods available today. The BQT can detect osteoporosis fracture risknoninvasively and inexpensively, and will allow primary carepractitioners to proactively manage osteoporosis diagnosis andtreatment.

Example 1 below demonstrates two means by which the state of proteins innails can be determined, i.e., nanoindentation and spectroscopicanalysis. The latter can be monitored using any spectroscopicmethodology, for example, Raman spectroscopy (as demonstrated below),NIR, and FT-IR, as noted elsewhere herein above. Example 2 describes theresults of a blind clinical trial undertaken to verify the specificityand sensitivity of the BQT based on Raman spectral analysis.

Example 1 Physical and Chemical Changes in Human Fingernails asCorrelates of Bone Disease

Two groups of subjects were identified. The first group (n=9) wasdiagnosed by DEXA (Lunar Prodigy, GE Medical systems), as osteoporotic(T score<−2.5). The second group (n=13) was diagnosed asnon-osteoporotic (T score>1.0). All statistical tests correlatingdisease to various dependent variables were performed using ANCOVA.

Fingernail clippings were obtained from all subjects. The nail apparatusis composed of the nail fold, nail matrix, nail bed, and thehyponychium, which together form the nail plate. This nail plate isproduced mainly by the matrix and emerges via the proximal nail fold,while being held in place by the lateral nail fold. It overlays the nailbed and detaches at the point called the hyponychium, or where the freeedge of the plate ends. This is where the clipping is taken (see FIG.1). This area corresponds to the area where high-sulfur keratin, typicalof hard keratins, is found. Following their sourcing, samples werestored in sealed specimen jars prior to testing.

Notably, the physical properties of fingernails change when soaked inwater, as it becomes soft and flexible. It is thought that the degree ofhydration is the most important factor influencing the physicalproperties of nails because chemically bound water is found in both dryand wet nails. The water-protein interaction changes the keratinstructure giving it new mechanical characteristics (Finlay et al. (1980)Br J. Dermatol. 103:357; and Wessel et al. (1999) Biochim Biophys Acta.1433:210). This highlights the need to store nail-clipping samples underconditions where they are not exposed to large amounts of water ordehydrated prior to testing. Accordingly, the nails were stored insealed jars not more than one month before testing.

Experiments performed on nails stored over time confirmed that nailsstored in the manner disclosed above maintained the same properties overat least a one month period. Specifically, nail samples were testedweekly over a period of one month for hardness and modulus to confirmthat no detectable changes had occurred. In contrast, nail samples thatwere tested one year after collection exhibited different properties.

Nanoindentation

The nails were trimmed prior to testing to expose the flat mid-sectionof each nail, and, therefore, reduce the possibility of the curved edgesof the nail making premature contact with the indenter. Samples werethen attached to aluminium stubs with an epoxy adhesive (part no: 46409,Versachem, Fla., USA).

Nanoindentation experiments were conducted using a laboratory-builtmachine previously described by Arteaga et al. (1993) Tribology Intl.26:305. For each indentation, the tip was brought into contact with thesurface using a load of a few μN. The load was then increased linearlyat 0.8 mNs⁻¹ up to its maximum value of 120 mN, and then reduced againat the same rate to zero. Every 150 ms during the cycle readings weretaken of the displacement of the indenter δ, and the load P, allowingthe examination of force-penetration data during both the loading andunloading phases. Consequently, it is possible to produce curves ofpenetration depth at each force level during the loading and unloadingphases. The data for these studies were generated using the Formulae1-3, supra. A schematic representation of a nanoindentation curve isgiven in FIG. 2. The collected data are shown in Table 1, and thestatistical analysis is shown in Table 2.

TABLE 1 Measurements of modulus and hardness of fingernail clippings.Max. Min. Sample Modulus Hardness Hardness BMD A(1) 3.43 0.247 0.236 2A(2) 3.09 0.186 0.164 2 A(3) 3.88 0.386 0.325 2 A(4) 3.38 0.23 0.201 2A(5) 3.47 0.298 0.256 2 G2(1) 3.25 0.201 0.173 2 G2(2) 3.14 0.202 0.1752 G2(3) 3.79 0.193 0.171 2 G2(4) 3.64 0.15 0.132 2 G2(5) 3.17 0.1940.172 2 H2(1) 2.95 0.266 0.234 2 H2(2) 4.51 0.497 0.424 2 H2(3) 4.110.415 0.352 2 H2(4) 6.24 0.614 0.522 2 H2(5) 3.62 0.219 0.189 2 D(1) 3.50.0693 0.0645 0 D(2) 3.34 0.0626 0.0565 0 D(3) 3.26 0.0578 0.0522 0 D(4)2.71 0.0407 0.0369 0 E(1) 4.34 0.299 0.268 0 E(2) 5.1 0.41 0.353 0 E(3)4.62 0.36 0.31 0 E(4) 4.86 0.388 0.337 0 E(5) 4.86 0.388 0.337 0 F(1)3.51 0.273 0.237 0 F(2) 3.33 0.293 0.253 0 F(3) 3.17 0.134 0.117 0 G(1)5.12 0.212 0.187 0 G(2) 5.27 0.345 0.3 0 G(3) 4.57 0.243 0.219 0 G(4)5.27 0.275 0.239 0 G(5) 5.79 0.351 0.302 0 H(1) 4.83 0.394 0.329 0 H(2)4.12 0.261 0.226 0 H(3) 4.36 0.265 0.224 0 H(4) 4.69 0.293 0.259 0 H(5)5.4 0.359 0.298 0 I(1) 2.47 0.12 0.109 0 I(2) 2.93 0.0536 0.0506 0 I(3)3.03 0.0756 0.0698 0 I(4) 2.8 0.135 0.122 0 I(5) 3.15 0.154 0.141 0 J(1)3.08 0.101 0.0885 0 J(2) 3.4 0.0762 0.0706 0 J(3) 2.82 0.0609 0.056 0J(4) 2.64 0.0782 0.0714 0 J(5) 3.83 0.125 0.112 0 K(1) 4.95 0.342 0.2950 K(2) 6.42 0.485 0.416 0 K(3) 5.48 0.415 0.356 0 K(4) 6.36 0.61 0.51 0K(5) 7.24 0.565 0.491 0 L(1) 3.45 0.309 0.263 0 L(2) 3.5 0.233 0.204 0L(3) 4.42 0.447 0.376 0 L(4) 3.94 0.31 0.27 0 N(1) 0.967 0.279 0.236 −3N(2) 1.27 0.275 0.237 −3 N(3) 0.933 0.145 0.131 −3 N(4) 1.49 0.297 0.255−3 N(5) 1.49 0.236 0.207 −3 O(1) 3.86 0.179 0.158 −3 O(2) 2.88 0.1240.112 −3 O(3) 2.53 0.073 0.0663 −3 O(4) 2.84 0.0987 0.0903 −3 O(5) 2.820.072 0.0672 −3 P(1) 1.83 0.121 0.103 −3 P(2) 1.63 0.148 0.128 −3 P(3)2.67 0.0898 0.0814 −3 P(4) 0.856 0.0503 0.0472 −3 Q(1) 1.41 0.04250.0405 −3 Q(2) 1.68 0.0768 0.0726 −3 Q(3) 1.49 0.133 0.121 −3 Q(4) 1.740.165 0.148 −3 Q(5) 1.97 0.183 0.161 −3 R(2) 5.06 0.376 0.324 −3 R(3)5.6 0.52 0.439 −3 R(4) 4.61 0.305 0.261 −3 R(5) 6.12 0.638 0.52 −3 S(1)3.02 0.0996 0.0908 −3 S(2) 4.47 0.37 0.324 −3 S(3) 3.58 0.21 0.185 −3S(4) 3.61 0.18 0.155 −3 S(5) 3.81 0.31 0.263 −3 T(1) 3.68 0.198 0.179 −3T(2) 3.58 0.137 0.125 −3 T(3) 4.01 0.295 0.251 −3 T(4) 2.99 0.148 0.134−3 T(5) 3.3 0.105 0.0978 −3 U(1) 2.27 0.172 0.153 −3 U(2) 1.21 0.1220.114 −3 U(3) 3.56 0.263 0.233 −3 U(4) 4.08 0.299 0.262 −3 U(5) 3.20.138 0.126 −3 V(1) 4.08 0.144 0.133 −3 V(2) 4.39 0.131 0.116 −3 V(3)6.23 0.458 0.398 −3 V(4) 4.33 0.142 0.134 −3 V(5) 3.75 0.277 0.242 −3

TABLE 2 Statistical analysis of collected data. High BMD Group meanmodulus 3.711333333 mean hardness 0.267467 standard deviation 0.81434344standard 0.121951 deviation Normal BMD Group mean modulus 4.193414634mean hardness 0.238365 standard deviation 1.162156637 standard 0.139288deviation Low BMD Group mean modulus 3.044093023 mean hardness 0.192416standard deviation 1.413736299 standard 0.117027 deviation All Non-Osteoporotic mean modulus 4.064285714 mean hardness 0.24616 standarddeviation 1.094289071 standard 0.134947 deviation

Mean elastic moduli and hardness results for the two sets of fingernailsare included below in Table 3.

TABLE 3 Mean moduli and hardness (and standard deviations) offingernails sourced. Subject Group Moduli (GPa) Hardness (GPa)Osteoporotic 3.0 (±1.5) 0.19 (±0.12) Healthy 4.1 (±1.1) 0.23 (±0.14)

The mean moduli of fingernails from patients with low BMD areapproximately 25% lower than those with normal BMD. The difference inmean modulus between the groups was found to be 1.1 GPa, which onlyapproached significance at 5% level (p=0.147) due to a lack of power(small n) within the test.

Raman Spectroscopy

For Raman analysis, four fingernail samples from each group wereanalysed to ascertain if there was disparity between groups, and todetect osteoporotic-induced changes in keratinized tissue. Micro Ramanspectra were obtained using a Dilor Labram 01 instrument. Excitation wasby red laser operating at 632.81 nm. Spectra were obtained by performing20 scans, to improve the signal-to-noise ratio, each with a laserexposure time of 50 seconds. The same operating procedure was repeatedfor all samples in order for the resultant spectra to show only thedifferences between the osteoporotic and non-osteoporotic tissue.Spectra were recorded from 300 cm⁻¹ to 1800 cm⁻¹ for identification ofall the characteristic peaks in human nail. The interval from 300 cm⁻¹to 700 cm¹ was selected for comparison. Normalization of all acquiredspectra was carried out to facilitate the comparison and to highlightdifferences between groups.

FIG. 3 shows the typical Raman spectrum of human nail between 300 cm⁻¹and 1800 cm⁻¹. The major spectral peaks of human nail include the amideband at 1677 cm⁻¹ indicating that nail keratin is predominantlyα-helical, the methylene (CH₂) deformation band at 1450 cm⁻¹ and theamide [ν(CN)] band at 1251 cm⁻¹. In the 1000 cm⁻¹ to 1200 cm¹ region thestrongest band occurs at 1006 cm⁻¹, corresponding to the C—C stretchingvibration of the aromatic ring in the phenylalanine side chain. However,it is the lower region of the spectrum that is of most concern in thisstudy. The area between 700 cm¹ and 300 cm⁻¹ contains the spectralinformation about the sulfur bonding in fingernails. The relativeintensities of the S-S and C-S stretching vibrations give a goodindication of the amount of sulfur present and allow determination ofthe structural configuration of the S—S bond. FIG. 3 shows the peak at510 cm⁻¹ representing the disulfide bonding [ν (SS)]. Lesser peaks at621 cm⁻¹ and 645 cm⁻¹ represent carbon sulfide bonding [ν (CS)].

FIG. 4 shows normalized Raman spectra for an osteoporotic andnon-osteoporotic nail on the same scale. Two main differences betweenosteoporotic and normal nails were observed. The disulfide bond (S—S,gauche-gauche-gauche conformation) peak for healthy nail at 510 cm⁻¹ wasmuch sharper than for the osteoporotic nail and the width of the S-Speak in osteoporotic nail was found to be larger than the healthy nail.Therefore, the disulfide bond content of the nails sourced fromosteoporotic patients was lower than those from healthy patients. Table4 shows that this difference in mean width at half maxima for the S—Speak from the two sets of nails is statistically significant (ANCOVA).

TABLE 4 Raman spectroscopy results for osteoporotic versusnon-osteoporotic nail. Width at half maxima for (cm⁻¹) (cm⁻¹) (cm⁻¹)Std. the S-S peak Minimum Maximum Mean Deviation Non-osteoporotic 25.0030.70 27.68 2.39 Osteoporotic 37.50 42.30 39.20 2.12

There was also a shift in the carbon sulfide bond (C—S) peak at about621 cm⁻¹ and 643 cm⁻¹ as shown by the higher wave numbers detected forthe C—S bonds in osteoporotic nail.

In protein spectra the C—S vibrational band originates from methionine,cysteine and cystine. Since methionine content in human nail isnegligible, the C—S and S—S bonds shown must have originated fromcysteine and cystine (Marshall et al. (1996) BMJ 312:1254). While notbeing bound by any particular mechanism or theory of action, the shiftin the carbon sulfide bonding may be due to the change of the sulfurcontent in the nails since it is known that the C—S stretching vibrationis dependent on the conformation of its side chains.

Example 2 Verification of Bone Quality Test Based on Raman SpectralAnalysis of Nails

The World Health Organization (WHO) defines osteoporosis as “a skeletaldisorder characterized by compromised bone strength predisposing aperson to an increased risk of fracture.” The WHO uses the bone mineraldensity (BMD) T-score as the standard for identifying the osteoporoticcondition. To obtain the T-score, an individual's BMD result (forexample, from DEXA) is compared with the BMD results from healthy 25-to35-year-old adults of the same sex and ethnicity. The standard deviation(SD) is the difference between your BMD and that of the healthy youngadults. This result is the “T-score.” Positive T-score values areindicative of bone that is stronger than normal; negative T-score valuesare indicative of bone that is weaker than normal. According to the WHO,osteoporosis is categorized based on the following bone mineral densitylevels:

-   -   A T-score within 1 SD (+1 or −1) of the young adult mean        indicates normal bone density;    -   A T-score of 1 to 2.4 SD below the young adult mean (−1 to −2.5        SD) indicates low bone mass;    -   A T-score of 2.5 SD or more below the young adult mean (greater        than −2.5 SD) indicates the presence of osteoporosis.        In general, the risk for bone fracture doubles with every SD        below normal. Thus, for example, a person with a T-score of −1        has twice the risk for bone fracture as a person with a normal        BMD. A person with a T-score of −2 has four times the risk for        bone fracture as a person with a normal BMD. When this        information is known, people with a high risk for bone fracture        can be treated with the goal of preventing future fractures.

The present example provides the results of a blind clinical trial thatwas carried out to identify women, based on the BQT, who were defined ashaving osteoporosis using the World Health Organization (WHO) definitionfor this condition (i.e., a BMD T-score of less than (i.e., morenegative than) or equal to −2.5 (e.g., −3.0). The sample size was 52patients, and the BQT data were obtained using Raman spectroscopy offingernail samples collected from these patients, and analyzing fordifferences in the Raman spectral peak at 510 cm⁻¹ (i.e., the S—S peak).

In this manner, fingernail clippings from these subjects were examinedusing Raman spectroscopy (spectra obtained with a Dilor Labram 01instrument) in a manner similar to that described in Example 1. For thisstudy, the width at half maxima (WHM) for the S-S peak from the Ramanspectrum was determined for nails collected from each individual, andthe relationships between T-score and age and T-score and WHM value inorder to evaluate T-score as a function of WHM and age. Results areshown in FIG. 5. Table 5 shows the number of non-osteoporotic andosteoporotic patients that had a high WHM value (i.e., 35 cm⁻¹ orgreater) and low WHM value (i.e., about 34 cm⁻¹ or less).

TABLE 5 Distribution of non-osteoporotic and osteoporotic patients basedon WHM value obtained from BQT using Raman spectral analysis of nails.Non-Osteoporotic Osteoporotic WHM High 1 28 WHM Low 21 2

Sensitivity of the BQT (i.e., the proportion of patients who testedpositive and have osteoporosis) was 93.3% (i.e., 28/30). Specificity ofthe BQT (i.e., the proportion of patients who tested negative and do nothave osteoporosis) was 95.5% (i.e., 21/22). Table 6 shows thecomparative sensitivity and specificity of the BQT and other diagnostictests to predict osteoporosis (i.e., a T-score≦−2.5)

TABLE 6 Comparison of BQT with other diagnostic tests to predict T score≦−2.5 Test Method Sensitivity Specificity BQT 93.3% 95.5% QUS 88%-100%  47% pDXA   94%   69% SCORE 65.7% 61.1% Questionnaire 93.3% 46.4%

For information regarding the use of these other diagnostic tests aspredictors of osteoporosis, see, for example, Naganathan et al. (1999)Med. J. Aust. 171:297-300 (quantative heel ultrasound (QUS)); Ross andSimon (1998) J. Bone Miner. Res. 23(suppl):S601, Rea et al. (2000)Osteoporos Int. 11(8):660-8, and Rea et al. (2000) J. Bone Miner. Res.15(3):564-74 (pDXA); Orthopaedic Nursing 24(1):33-39 (SCORE), andCadarette et al. (2000) C.M.A.J. 162(9):1289-94 (Questionnaire).

These results indicate that a positive result on the BQT is equivalentto a DEXA T-score of −2.5 or less, and treatment should be consideredaccordingly.

In another assessment of the predictive value of the BQT, the fracturerisk as a function of the bone quality score and age was determined fora subset of the women participating in this trial. As can be seen fromFIG. 6, women with fracture histories have very different bone qualityscores (WHM score value over about 36 cm⁻¹) from women with no fracturehistory (WHM score value below about 34 cm⁻¹).

Thus Raman spectroscopy of nails, either in situ or as nail clippings,can assess fracture risk in a more rapid and less expensive manner thatavoids potential problems associated with radiation assessment. Further,a desktop Raman spectroscopy apparatus such as that described in Example3 below, could be made readily available to practitioners to supportmass screening of subjects for the presence or absence of a disease suchas osteoporosis, to follow treatment efficacy of individuals having orat risk of developing a bone disease such as osteoporosis, and topredict fracture risk. A reduction in fractures based on more screeningand preventative treatment could have significant health and economicbenefits worldwide and expand the osteoporosis preventative drug marketconsiderably.

Example 3 Raman Spectroscopy Apparatus for Assessing Osteoporosis andFracture Risk

Any commercially available Raman spectroscopy system can be utilized inthe diagnostic assays described herein. FIG. 7 illustrates the maincomponents that can be found within such a system for use in conductingRaman spectral analysis of a keratinized tissue such as nail, either insitu or as nail clippings. The components can be assembled as part of anindividual package, or can be constructed as multiple units that areintegrated for operation and spectral analysis. In order to collect thespectral data, a probe is placed against the nail of a subject, forexample, an intact fingernail of a finger, and a beam of light from thelight source is delivered to the nail surface, for example, by pressinga button on the apparatus. The light delivery time can vary, but can beas short as 2-5 seconds. Following spectral selection for Ramanscattered light, detection of the Raman scattered light, andquantification, the spectral result is displayed, for example, on ascreen, and can then be written to a chip with a data stamp.

Many modifications and other embodiments of the inventions set forthherein will come to mind to one skilled in the art to which theseinventions pertain having the benefit of the teachings presented in theforegoing descriptions and the associated drawings. Therefore, it is tobe understood that the inventions are not to be limited to the specificembodiments disclosed and that modifications and other embodiments areintended to be included within the scope of the appended claims.Although specific terms are employed herein, they are used in a genericand descriptive sense only and not for purposes of limitation.

All publications and patent applications mentioned in the specificationare indicative of the level of those skilled in the art to which thisinvention pertains. All publications and patent applications are hereinincorporated by reference to the same extent as if each individualpublication or patent application was specifically and individuallyindicated to be incorporated by reference.

The invention claimed is:
 1. A method of diagnosing a bone disease in asubject, the method comprising: obtaining a keratinized tissue samplefrom a subject; using a Raman spectrometer to obtain a Raman signal anda Rayleigh scattered light signal from the sample; separating the Ramansignal from the Rayleigh scattered light signal; using a computer tonormalize the Raman signal, thereby producing a normalized Raman signal;using the computer to measure a level of sulfur bonding indicated by atleast one peak in the normalized Raman signal to make a positive ornegative diagnosis of the bone disease; and using the computer togenerate an output that is indicative of the positive or negativediagnosis of the bone disease.
 2. The method of claim 1, wherein thekeratinized tissue sample is a nail clipping.
 3. The method of claim 1,wherein the Raman signal covers between 300 cm⁻¹ and 1800 cm⁻¹.
 4. Themethod of claim 1, wherein obtaining the Raman signal comprises using alaser light source.
 5. The method of claim 1, wherein the at least onepeak is at 510 cm⁻¹.
 6. The method of claim 5, wherein the measuring isaccomplished by a technique that is selected from a group consisting of:comparison of a width at half maximum of the peak, comparison of arelative peak height, and area integration under the peak.
 7. The methodof claim 5, wherein the bone disease is osteoporosis.
 8. The method ofclaim 7, wherein the measuring is accomplished by area integration underthe peak.
 9. The method of claim 7, wherein the measuring isaccomplished by comparison of a relative peak height.
 10. The method ofclaim 1, wherein the bone disease is osteoporosis.